Aspect Level Sentiment Analysis on Zoom Cloud Meetings App Review Using LDA

Aspect Level Sentiment Analysis on Zoom Cloud Meetings App Review Using LDA

LDA, SVM, review, aspect

During the Covid-19 pandemic,almost all community activities are conducted from home.Therefore, video conference technology is needed for people to carry out their normal activities from home. One of the video conference applications is ZOOM Cloud Meetings. Applications certainly havebeen reviewedgiven by theirusers as a reference for new users andcompanies of the application to know the application’s performance. However, in reviews, some constraints are the number of reviews as well as irregular. Therefore, a solution is needed with sentiment analysis that aims to classify the reviews of the application to be organized by categorizing positive or negative sentiment. In this study, aspect-based sentiment analysis was conducted on ZOOM Cloud Meetings app reviews from Google Play Store. The analysis’s resultof the review data obtained threeaspects,namely aspects of usability, system, and appearance. The modeling topic used istheLatent Dirichlet Allocation(LDA) method and classification using the Support Vector Machine (SVM). This research resulted in the best performance with the best parametersresulting in the performance accuracy of usability aspect is 88.83%, system aspect with 91.2%, appearance aspect with 94.78%, and performance accuracy of all aspects 91.61%

Janu Akrama Wardhana1, Yuliant Sibaroni

https://jurnal.iaii.or.id/index.php/RESTI/issue/view/24

Telkom University

20 agustus 2021

Fajar bagus W

PDF

Indonesia

Text